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2013 18th International Conference on Digital Signal Processing (DSP)最新文献

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Image Super-Resolution reconstruction based on adaptive gradient field sharpening 基于自适应梯度场锐化的图像超分辨率重建
2013 18th International Conference on Digital Signal Processing (DSP) Pub Date : 2013-07-01 DOI: 10.1109/ICDSP.2013.6622831
Ting Li, P. Papamichalis
{"title":"Image Super-Resolution reconstruction based on adaptive gradient field sharpening","authors":"Ting Li, P. Papamichalis","doi":"10.1109/ICDSP.2013.6622831","DOIUrl":"https://doi.org/10.1109/ICDSP.2013.6622831","url":null,"abstract":"The Super-Resolution (SR) image reconstruction is a computational technique that improves the resolution of an image system. In this paper we propose a new method for multi-image SR reconstruction, which is capable of producing sharper images with clearer image details. A two-step method is used. The first step is conventional SR image reconstruction. From this preliminary result, an image gradient is determined and transformed to increase the sharpness, and then it is included into the second reconstruction as a prior to get the final result. The Gradient Profile prior [4] is used in the gradient transform for sharpness enhancement. Results demonstrate the effectiveness of the proposed method to produce sharp and clear images from low-resolution images.","PeriodicalId":180360,"journal":{"name":"2013 18th International Conference on Digital Signal Processing (DSP)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123356142","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Super-resolution using neighbor embedding of back-projection residuals 利用邻域嵌入反投影残差的超分辨率
2013 18th International Conference on Digital Signal Processing (DSP) Pub Date : 2013-07-01 DOI: 10.1109/ICDSP.2013.6622796
M. Bevilacqua, A. Roumy, C. Guillemot, Marie-Line Alberi-Morel
{"title":"Super-resolution using neighbor embedding of back-projection residuals","authors":"M. Bevilacqua, A. Roumy, C. Guillemot, Marie-Line Alberi-Morel","doi":"10.1109/ICDSP.2013.6622796","DOIUrl":"https://doi.org/10.1109/ICDSP.2013.6622796","url":null,"abstract":"In this paper we present a novel algorithm for neighbor embedding based super-resolution (SR), using an external dictionary. In neighbor embedding based SR, the dictionary is trained from couples of high-resolution and low-resolution (LR) training images, and consists of pairs of patches: matching patches (m-patches), which are used to match the input image patches and contain only low-frequency content, and reconstruction patches (r-patches), which are used to generate the output image patches and actually bring the high-frequency details. We propose a novel training scheme, where the m-patches are extracted from enhanced back-projected interpolations of the LR images and the r-patches are extracted from the back-projection residuals. A procedure to further optimize the dictionary is followed, and finally nonnegative neighbor embedding is considered at the SR algorithm stage. We consider singularly the various elements of the algorithm, and prove that each of them brings a gain on the final result. The complete algorithm is then compared to other state-of-the-art methods, and its competitiveness is shown.","PeriodicalId":180360,"journal":{"name":"2013 18th International Conference on Digital Signal Processing (DSP)","volume":"213 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121720333","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 17
Mixed structural modeling of head-related transfer functions for customized binaural audio delivery 用于定制双耳音频传输的头部相关传递函数的混合结构建模
2013 18th International Conference on Digital Signal Processing (DSP) Pub Date : 2013-07-01 DOI: 10.1109/ICDSP.2013.6622764
M. Geronazzo, Simone Spagnol, F. Avanzini
{"title":"Mixed structural modeling of head-related transfer functions for customized binaural audio delivery","authors":"M. Geronazzo, Simone Spagnol, F. Avanzini","doi":"10.1109/ICDSP.2013.6622764","DOIUrl":"https://doi.org/10.1109/ICDSP.2013.6622764","url":null,"abstract":"A novel approach to the modeling of head-related transfer functions (HRTFs) for binaural audio rendering is formalized and described in this paper. Mixed structural modeling (MSM) can be seen as the generalization and extension of the structural modeling approach first defined by Brown and Duda back in 1998. Possible solutions for building partial HRTFs (pHRTFs) of the head, torso, and pinna of a specific listener are first described and then used in the construction of two possible mixed structural models of a KEMAR mannequin. Thanks to the flexibility of the MSM approach, an exponential number of solutions for building custom binaural audio displays can be considered and evaluated, the final aim of the process being the achievement of a HRTF model fully customizable by the listener.","PeriodicalId":180360,"journal":{"name":"2013 18th International Conference on Digital Signal Processing (DSP)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132778001","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 27
Efficient intra-frame video coding for low resolution wireless visual sensors 低分辨率无线视觉传感器的高效帧内视频编码
2013 18th International Conference on Digital Signal Processing (DSP) Pub Date : 2013-07-01 DOI: 10.1109/ICDSP.2013.6622809
Weiwei Chen, Frederik Verbist, N. Deligiannis, P. Schelkens, A. Munteanu
{"title":"Efficient intra-frame video coding for low resolution wireless visual sensors","authors":"Weiwei Chen, Frederik Verbist, N. Deligiannis, P. Schelkens, A. Munteanu","doi":"10.1109/ICDSP.2013.6622809","DOIUrl":"https://doi.org/10.1109/ICDSP.2013.6622809","url":null,"abstract":"This paper proposes a low-complexity intra-frame video coding system for very low resolution sequences. The application focuses on power constrained wireless visual sensors, recording extremely low-resolution video, namely, 30×30 pixels. In the proposed framework, high-performance video coding techniques such as block-based transforms, intra prediction and entropy coding are employed. The proposed system features several different configurations, all of which are evaluated both in terms of coding efficiency and computational complexity. Based on the experimental results, the best configuration is identified. Experimental results show that the proposed configuration achieves better coding performance than the H.264/AVC Intra frame codec, at only 23.7% of its encoding complexity.","PeriodicalId":180360,"journal":{"name":"2013 18th International Conference on Digital Signal Processing (DSP)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130755708","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
Multimodal desktop interaction: The face - object - gesture - voice example 多模式桌面交互:脸-对象-手势-声音的例子
2013 18th International Conference on Digital Signal Processing (DSP) Pub Date : 2013-07-01 DOI: 10.1109/ICDSP.2013.6622782
N. Vidakis, A. Vlasopoulos, Tsampikos Kounalakis, Petros Varchalamas, M. Dimitriou, Grigorios Kalliatakis, Efthimios Syntychakis, John Christofakis, G. Triantafyllidis
{"title":"Multimodal desktop interaction: The face - object - gesture - voice example","authors":"N. Vidakis, A. Vlasopoulos, Tsampikos Kounalakis, Petros Varchalamas, M. Dimitriou, Grigorios Kalliatakis, Efthimios Syntychakis, John Christofakis, G. Triantafyllidis","doi":"10.1109/ICDSP.2013.6622782","DOIUrl":"https://doi.org/10.1109/ICDSP.2013.6622782","url":null,"abstract":"This paper presents a natural user interface system based on multimodal human computer interaction, which operates as an intermediate module between the user and the operating system. The aim of this work is to demonstrate a multimodal system which gives users the ability to interact with desktop applications using face, objects, voice and gestures. These human behaviors constitute the input qualifiers to the system. Microsoft Kinect multi-sensor was utilized as input device in order to succeed the natural user interaction, mainly due to the multimodal capabilities offered by this device. We demonstrate scenarios which contain all the functions and capabilities of our system from the perspective of natural user interaction.","PeriodicalId":180360,"journal":{"name":"2013 18th International Conference on Digital Signal Processing (DSP)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131030169","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
Optimization of the set of path-rays in linear tomography 线性层析成像中路径射线集的优化
2013 18th International Conference on Digital Signal Processing (DSP) Pub Date : 2013-07-01 DOI: 10.1109/ICDSP.2013.6622754
S. Carcangiu, A. Montisci, Marco Raugi, M. Tucci
{"title":"Optimization of the set of path-rays in linear tomography","authors":"S. Carcangiu, A. Montisci, Marco Raugi, M. Tucci","doi":"10.1109/ICDSP.2013.6622754","DOIUrl":"https://doi.org/10.1109/ICDSP.2013.6622754","url":null,"abstract":"In this work a new formalization of selecting the optimal set of path-rays problem in linear tomography is presented. In particular the problem of selecting the optimal set of path-rays is formalized as a problem of selecting a sub-matrix of a matrix with certain spectral properties, which is known to be an NP-hard problem. New criteria of optimality of the set of path-rays are introduced, and an optimization algorithm is proposed to deal with the combinatory search problem. The obtained results are compared to those of existing approximation algorithms. Numerical results show that the optimal solutions yielded by the proposed optimization algorithm, outperform existing algorithms in terms of conditioning of the tomography linear equations system.","PeriodicalId":180360,"journal":{"name":"2013 18th International Conference on Digital Signal Processing (DSP)","volume":"2 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133002454","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
A fast matching algorithm for asymptotically optimal distributed channel assignment 渐近最优分布式信道分配的快速匹配算法
2013 18th International Conference on Digital Signal Processing (DSP) Pub Date : 2013-07-01 DOI: 10.1109/ICDSP.2013.6622738
O. Naparstek, Amir Leshem
{"title":"A fast matching algorithm for asymptotically optimal distributed channel assignment","authors":"O. Naparstek, Amir Leshem","doi":"10.1109/ICDSP.2013.6622738","DOIUrl":"https://doi.org/10.1109/ICDSP.2013.6622738","url":null,"abstract":"The channel assignment problem is a special case of a very well studied combinatorial optimization problem known as the assignment problem. In this paper we introduce an asymptotically optimal fully distributed algorithm for the maximum cardinality matching problem. We show that with high probability, the running time of the algorithm on random bipartite graphs is less than O (N log(N)/log Np)) . We then show that the proposed algorithm can be used to produce asymptotically optimal solutions for the max sum assignment problem.","PeriodicalId":180360,"journal":{"name":"2013 18th International Conference on Digital Signal Processing (DSP)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124346154","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 12
Accurate reconstruction of noisy medical images using orthogonal moments 利用正交矩精确重建有噪医学图像
2013 18th International Conference on Digital Signal Processing (DSP) Pub Date : 2013-07-01 DOI: 10.1109/ICDSP.2013.6622675
K. Hosny, G. Papakostas, D. Koulouriotis
{"title":"Accurate reconstruction of noisy medical images using orthogonal moments","authors":"K. Hosny, G. Papakostas, D. Koulouriotis","doi":"10.1109/ICDSP.2013.6622675","DOIUrl":"https://doi.org/10.1109/ICDSP.2013.6622675","url":null,"abstract":"Accurate reconstruction of noisy medical images is presented in this work. Speckle, additive white Gaussian and Rician noises are the most popular kinds of noise raised in medical imaging systems. Medical images contaminated with these noises were reconstructed herein by using Pseudo Zernike, Legendre, Gaussian-Hermite, and Krawtchouk moments. Numerical experiments were conducted and the moments' performance in reconstructing the noisy medical images was evaluated. The experiments have shown that the performance of Legendre moments is superior to all other moments in the case of speckle and Rician noises, while in the case of additive Gaussian noise, Legendre, Gaussian-Hermite and Krawtchouk moments presenting very similar performances.","PeriodicalId":180360,"journal":{"name":"2013 18th International Conference on Digital Signal Processing (DSP)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115095263","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 16
Reflectance analysis based countermeasure technique to detect face mask attacks 基于反射分析的掩码攻击检测技术
2013 18th International Conference on Digital Signal Processing (DSP) Pub Date : 2013-07-01 DOI: 10.1109/ICDSP.2013.6622704
N. Kose, J. Dugelay
{"title":"Reflectance analysis based countermeasure technique to detect face mask attacks","authors":"N. Kose, J. Dugelay","doi":"10.1109/ICDSP.2013.6622704","DOIUrl":"https://doi.org/10.1109/ICDSP.2013.6622704","url":null,"abstract":"Face photographs, videos or masks can be used to spoof face recognition systems. Recent studies show that face recognition systems are vulnerable to these attacks. In this paper, a countermeasure technique, which analyzes the reflectance characteristics of masks and real faces, is proposed to detect mask attacks. There are limited studies on countermeasures against mask attacks. The reason for this delay is mainly due to the unavailability of public mask attack databases. In this study, a 2D+3D face mask attack database is used which is prepared for a research project in which the authors are all involved. The performance of the countermeasure is evaluated using the texture images which were captured during the acquisition of 3D scans. The results of the proposed countermeasure outperform the results of existing techniques, achieving a classification accuracy of 94.47%. In this paper, it is also proved that reflectance analysis may provide more information for the purpose of mask spoofing detection compared to texture analysis.","PeriodicalId":180360,"journal":{"name":"2013 18th International Conference on Digital Signal Processing (DSP)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117219712","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 52
Tensor dictionary learning with sparse TUCKER decomposition 稀疏TUCKER分解的张量字典学习
2013 18th International Conference on Digital Signal Processing (DSP) Pub Date : 2013-07-01 DOI: 10.1109/ICDSP.2013.6622725
S. Zubair, Wenwu Wang
{"title":"Tensor dictionary learning with sparse TUCKER decomposition","authors":"S. Zubair, Wenwu Wang","doi":"10.1109/ICDSP.2013.6622725","DOIUrl":"https://doi.org/10.1109/ICDSP.2013.6622725","url":null,"abstract":"Dictionary learning algorithms are typically derived for dealing with one or two dimensional signals using vector-matrix operations. Little attention has been paid to the problem of dictionary learning over high dimensional tensor data. We propose a new algorithm for dictionary learning based on tensor factorization using a TUCKER model. In this algorithm, sparseness constraints are applied to the core tensor, of which the n-mode factors are learned from the input data in an alternate minimization manner using gradient descent. Simulations are provided to show the convergence and the reconstruction performance of the proposed algorithm. We also apply our algorithm to the speaker identification problem and compare the discriminative ability of the dictionaries learned with those of TUCKER and K-SVD algorithms. The results show that the classification performance of the dictionaries learned by our proposed algorithm is considerably better as compared to the two state of the art algorithms.","PeriodicalId":180360,"journal":{"name":"2013 18th International Conference on Digital Signal Processing (DSP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125747617","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 77
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